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Author:

Jiang, Zongli (Jiang, Zongli.) (Scholars:蒋宗礼) | Deng, Yi (Deng, Yi.)

Indexed by:

EI Scopus

Abstract:

In a variety of text classification algorithm, KNN is a competitive one with simple implementation and high efficiency. However, with the expansion of the size of the text, the runtime of KNN will grow rapidly that cannot be afford. In this paper, we improve the KNN by introducing the kd-tree storage structure and reducing the sample space through the sample clestering methods. And experiment shows that the runtime of improved KNN algorithm reduce apparently. ©2010 IEEE.

Keyword:

Text processing Classification (of information) Clustering algorithms Learning algorithms

Author Community:

  • [ 1 ] [Jiang, Zongli]School of Computer Science and Engineering, Beijing University of Technology, 100124, Beijing, China
  • [ 2 ] [Deng, Yi]School of Computer Science and Engineering, Beijing University of Technology, 100124, Beijing, China

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Source :

Year: 2010

Volume: 2

Page: V2317-V2321

Language: English

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 2

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 9

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